Triple
T30827688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Back River, Maryland |
E785120
|
entity |
| Predicate | hasAdjacentLandcover |
P85343
|
FINISHED |
| Object | wetlands |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: wetlands | Statement: [Back River, Maryland, hasAdjacentLandcover, wetlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentLandcover Context triple: [Back River, Maryland, hasAdjacentLandcover, wetlands]
-
A.
hasNearbyLandscapeType
chosen
Indicates that one entity is located close to, or in the vicinity of, a particular type of landscape.
-
B.
surroundedByLandUse
Indicates that an area or feature is encircled or bordered on all sides by specified types of land use.
-
C.
hasNeighboringFeature
Indicates that one feature is located adjacent to or directly next to another feature in space.
-
D.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
E.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: April 29, 2026, 8:44 p.m.